Combined use of conventional and second-derivative data in the SIMPLISMA self-modeling mixture analysis approach.

@article{Windig2002CombinedUO,
  title={Combined use of conventional and second-derivative data in the SIMPLISMA self-modeling mixture analysis approach.},
  author={Willem Windig and Brian Antalek and Joseph L Lippert and Yann Batonneau and Claude Br{\'e}mard},
  journal={Analytical chemistry},
  year={2002},
  volume={74 6},
  pages={1371-9}
}
Simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) is a successful pure variable approach to resolve spectral mixture data. A pure variable (e.g., wavenumber, frequency number, etc.) is defined as a variable that has significant contributions from only one of the pure components in the mixture data set. For spectral data with highly overlapping pure components or significant baselines, the pure variable approach has limitations; however, in this case, second-derivative spectra… CONTINUE READING

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